This invention relates to an equipment for automatically classifying a picked fingerprint pattern.
Fingerprint identification can be used for identifying individuals, for example, in an access control system. And in order to minimize the identification time, fingerprints are classified into several patterns.
Generally, a ridge direction pattern is used for fingerprint classification. A fingerprint image picture is subdivided into a matrix of equally shaped rectangles called zones. In each zone, an average direction of ridge lines is estimated and the estimated average direction is quantized to determine a direction label of the zone. A matrix of direction labels of the zones represents the ridge direction pattern of the fingerprint image picture.
Gotoh et al. proposed a method of matching to reference ridge direction patterns prepared beforehand, on "Fingerprint Image Classification by Ridge Direction Distribution." in IE81-88, Technical Report of Japanese Electrical Communication vol. 18, no. 210. On "Fingerprint Pattern Classifier" in Treatise of Japanese Electronics and Electrical Communication, Noda et al. proposed a method of pattern classification in accordance with delta data, that is, existence, numbers, and position coordinates of deltas. Here a delta means a triangle formed by a combination of ridge direction Labels. Noda et al. considered a matrix of ridge direction labels as a vector field, and from a line integration of the rotation of the field and an areal integration of the divergence of the field, determined feature points including the center of a fingerprint called core, and the deltas.
In these aforementioned methods, the delta has been an important factor for fingerprint pattern classification. However, it is sometimes difficult to pick up deltas owing to their positions in the fingerprint. Especially, in a fingerprint pattern recognizer used for criminal investigation where lost fingerprints are to be classified, delta missing fingerprints are frequently treated and the use of the delta data has usually been difficult.
And in a method of fingerprint pattern classification where no feature point is employed, there has been a problem of misjudgment owing to noises produced from flaws and wrinkles in a fingerprint image picture.